12 research outputs found
⚘ A semiotic analysis of philosophy as expressed in urban space: The case of ancient Greece ☀ Alexandros Ph. Lagopoulos
No full text<p>Leverage your erudition... and you will be well versed in precious findings on the ways of philosophizing among the ancients in the tongue of Homer.</p>
<p>This event, commented by Olga Lavrenova (International Association for Semiotics of Space and Time) and chaired by William Passarini (Institute for Philosophical Studies), is part of the activities of the 2022 International Open Seminar on Semiotics: a Tribute to John Deely on the Fifth Anniversary of His Passing, cooperatively organized by the Institute for Philosophical Studies of the Faculty of Arts and Humanities of the University of Coimbra, the Lyceum Institute, the Deely Project, Saint Vincent College, the Iranian Society for Phenomenology at the Iranian Political Science Association, the International Association for Semiotics of Space and Time, the Institute for Scientific Information on Social Sciences of the Russian Academy of Sciences, the Semiotic Society of America, the American Maritain Association, the International Association for Semiotic Studies, the International Society for Biosemiotic Studies, the International Center for Semiotics and Intercultural Dialogue, Moscow State Academic University for the Humanities and the Mansarda Acesa with the support of the FCT - Foundation for Science and Technology, I.P., of the Ministry of Science, Technology and Higher Education of the Government of Portugal under the UID/FIL/00010/2020 project.</p>
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<p>Alexandros Lagopoulos is Professor Emeritus of Urban Planning at Aristotle University of Thessaloniki, Greece, and Corresponding Member of the Academy of Athens. He holds a postgraduate diploma from the Centre de Recherche d’Urbanisme, Paris. He has a doctorate in Engineering and a post-doctoral academic title (Habilitation) in Urban and Regional Planning from the National Technical University of Athens, a doctorate in Social Anthropology from the Sorbonne and an honorary doctorate in Semiotics from the New Bulgarian University of Sofia. He has been vice-president of the International Association for Semiotic Studies and is honorary president of the Hellenic Semiotic Society and the International Association for the Semiotics of Space+Time. He is the author of many books and articles in Greek, English, and French, as well as some in German, Russian, and Bulgarian.</p>
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<p>Olga Lavrenova (1969), Russian geographer, philosopher, historian. DSc (Philosophy), PhD (Geography). She is a leading researcher of the Institute for Scientific Information on Social Sciences of the Russian Academy of Sciences (INION RAN, in Russian), professor at the National University of Science and Technology (MISiS) and at the GITR Film and Television School. She is also Deputy Director for Science at the Nicholas Roerich Museum of the International Centre of the Roerichs, President of the International Association for Semiotics of Space and Time (IASSp+T, Switzerland), and Honorary Member of the Russian Academy of Arts. Fulbright grantee (2021) at the University of North Carolina at Chapel Hill and the University of Texas at Austin. Author of over 180 publications, including the monograph: Spaces and Meanings: Semantics of the Cultural Landscape (Springer, 2019). She is the author of the long-term interdisciplinary scientific project “The Geography of Art” (since 1992, 10 collections were published and 7 conferences were held). The project considers the territorial problems of culture and art, reflected in the art of the geographical space, the role of regional factors in the formation of art schools and artworks. Particular attention is given to topics such as artistic perception of the cultural landscape, the place of art in shaping the cultural landscape and the image of the territory, as well as the concepts of space in works of art. She is also the author of the long-term interdisciplinary scientific project “Russia and the East: the interaction in art” (since 2018, 2 conferences were held and 1 collection was published).</p>
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<p>Homepage: https://www.uc.pt/fluc/uidief/act/io2s<br>
Auditorium: https://www.uc.pt/fluc/uidief/act/io2s/auditorium</p>
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<p>Technical support assured by Robert Junqueira.</p>
<p>The official graphic designer of the IO2S DEELY is Zahra Soltani Tehrani.</p>
Ανακάλυψη γνώσης από επιστημονικές δημοσιεύσεις
No full textThis thesis presents original research in the area of information and library sciences, and more specifically in the field of knowledge discovery from academic publications. Knowledge discovery from academic publications brings together multiple tasks from different research fields, such as information retrieval, machine learning, and natural language processing, and aims to understand, advance, and use the published scientific materials to address more effectively the problems of our society. The products of this research field are novel algorithms and methods that explore, analyze and use the information found in scholarly data more effectively, faster, and with ease. Our contribution concerns knowledge discovery from academic publications in four different tasks: total recall retrieval, semantic indexing, accessing bibliographic resources, and analyzing self-citations. The common elements in these tasks are the use of raw data derived from publications and the introduction of novel machine learning approaches. The dissertation’s application domain is academic publications; however, the developed methods could easily be applied to other fields where text documents are the main data source. First, we present a novel approach for document screening prioritization that aims to help researchers create systematic literature reviews. Our approach retrieves and efficiently ranks documents based on a given query, employing learning-to-rank techniques along with an iterative feedback method. Second, we introduce a multi-label approach for classifying biomedical figures. This method doesn't use a figure separation algorithm and utilizes both visual and textual features. Third, we propose an innovative web robot detection approach that takes into account the content of a website. Our main contribution is a novel representation for web sessions, based on LDA, that quantifies the semantic variance of the web content requested within a session. Finally, we present a new way for detecting potentially unethical self-citations based on the semantic similarity of a publication and its references. The ReLy score is introduced, which is based on state-of-the-art sentence embeddings and quantifies that quantifies the semantic similarity of article-reference. All the above approaches are evaluated and compared against the relevant state-of-the-art, in multiple experimental settings and with real-world data. The results demonstrate significant improvements or new findings in all cases. We also publish, in many cases, the datasets used to encourage transparency and future research.Αυτή η διατριβή παρουσιάζει πρωτότυπη έρευνα στους τομείς των επιστημών της πληροφορικής και της βιβλιοθηκονομίας, και συγκεκριμένα στον τομέα της ανακάλυψης γνώσης από ακαδημαϊκές δημοσιεύσεις. Η ανακάλυψη γνώσης από ακαδημαϊκές δημοσιεύσεις συγκεντρώνει πολλαπλά ερωτήματα από διαφορετικά ερευνητικά πεδία, όπως ανάκτηση πληροφοριών, μηχανική μάθηση και επεξεργασία φυσικής γλώσσας, και στοχεύει στην κατανόηση, προώθηση και χρήση του δημοσιευμένου επιστημονικού υλικού για την αποτελεσματικότερη αντιμετώπιση των προβλημάτων της κοινωνίας μας. Τα προϊόντα αυτού του ερευνητικού πεδίου είναι νέοι αλγόριθμοι και μέθοδοι που διερευνούν, αναλύουν και χρησιμοποιούν τις πληροφορίες που βρίσκονται στις επιστημονικές δημοσιεύσεις πιο αποτελεσματικά, γρηγορότερα και με ευκολία. Η συμβολή μας αφορά την ανακάλυψη γνώσης από ακαδημαϊκές εκδόσεις σε τέσσερις διαφορετικά προβλήματα: ανάκτηση ολικής ανάκλησης, σημασιολογική δεικτοδότηση, πρόσβαση σε βιβλιογραφικές πηγές και ανάλυση αυτό-παραπομπών. Τα κοινά στοιχεία σε αυτές τις εργασίες είναι η χρήση ακατέργαστων δεδομένων που προέρχονται από δημοσιεύσεις και η ανάπτυξη νέων μεθόδων μηχανικής μάθησης. Ο τομέας εφαρμογής της διατριβής είναι οι ακαδημαϊκές δημοσιεύσεις αλλά οι μέθοδοι που αναπτύχθηκαν μπορούν εύκολα να εφαρμοστούν σε άλλα πεδία όπου τα έγγραφα κειμένου είναι η κύρια πηγή δεδομένων. Πρώτον, παρουσιάζουμε μια νέα προσέγγιση για την αξιολόγηση εγγράφων που στοχεύει να βοηθήσει τους ερευνητές να δημιουργήσουν συστηματικές βιβλιογραφικές ανασκοπήσεις. Η προσέγγισή μας ανακτά και κατατάσσει αποτελεσματικά έγγραφα με βάση ένα ερώτημα, χρησιμοποιώντας τεχνικές learning-to-rank μαζί με μια επαναληπτική μέθοδο ανατροφοδότησης. Δεύτερον, παρουσιάζουμε μια προσέγγιση πολλαπλών ετικετών για την ταξινόμηση βιοϊατρικών εικόνων. Αυτή η μέθοδος δεν χρησιμοποιεί έναν αλγόριθμο διαχωρισμού εικόνων και χρησιμοποιεί οπτικά χαρακτηριστικά καθώς και χαρακτηριστικά κειμένου. Τρίτον, προτείνουμε μια καινοτόμο προσέγγιση εντοπισμού ρομπότ του διαδικτύου που λαμβάνει υπόψη το περιεχόμενο ενός ιστότοπου. Η κύρια συνεισφορά μας είναι μια νέα αναπαράσταση για διαδικτυακές συνεδρίες, βασισμένη στο LDA, που ποσοτικοποιεί τη σημασιολογική διακύμανση του περιεχομένου ιστού μιας συνεδρίας. Τέλος, παρουσιάζουμε έναν νέο τρόπο ανίχνευσης δυνητικά μη θεμιτών αυτό-παραπομπών με βάση τη σημασιολογική ομοιότητα μιας εργασίας και των παραπομπών αυτής. Παρουσιάζουμε τη βαθμολογία ReLy, η οποία βασίζεται σε sentence embeddings και ποσοτικοποιεί τη σημασιολογική ομοιότητα άρθρου-παραπομπής. Όλες οι παραπάνω προσεγγίσεις αξιολογούνται και συγκρίνονται με αντίστοιχες κορυφαίες μεθόδους, σε πολλαπλές πειραματικές ρυθμίσεις και με δεδομένα που προέρχονται από τον πραγματικό κόσμο. Τα αποτελέσματα καταδεικνύουν σημαντικές βελτιώσεις ή νέα ευρήματα σε όλες τις περιπτώσεις και δημοσιεύουμε, σε πολλές περιπτώσεις, τα σύνολα δεδομένων που χρησιμοποιούνται για ενθάρρυνση της διαφάνειας και της μελλοντικής έρευνας
Using multi-target feature evaluation to discover factors that affect business process behavior
No full textCertain business environments, like health-care or customer service, host complex and highly variable business processes. In such situations, we expect fluctuating process behavior, which is difficult to attribute to specific causes, at least automatically. This work aims to provide process analysts with an additional tool to discover factors that affect the process flow. To this end, we propose a three-stage methodology to deal with the several challenges of this goal.Adhering to the process mining paradigm that suggests for evidence-based process analysis and improvement, we introduce a horizontal partitioning approach to identify elements of process behavior during the first stage. Then, during the second stage, we discuss how log manipulations can yield characteristics that reflect various perspectives of the process. Finally, we propose a multi-target feature evaluation step to deliver insights about the associations between characteristics and process behavior.The proposed methodology is designed to tackle challenges related to the general correlation problem of process mining, like dealing with general process behavior (not just local decisions) and relaxing the independence assumption among the elements of behavior. We demonstrate our approach step by step through a case study on a real-world, open dataset
The N-methyl-d-aspartate receptor as a neurobiological intersection between bipolar disorder and alcohol use: A longitudinal mismatch negativity study
No full textBackground: Comorbid risky alcohol use in bipolar disorder (BD) is recognized for its high prevalence and clinical relevance, though understanding of its neurobiological underpinning is limited. The N-methyl-D-aspartate (NMDA) receptor has recognized alterations in BD and is a major site of ethanol's effects in the brain. The present study aimed to examine the NMDA receptor system in adolescents and young adults with BD by evaluating the longitudinal changes in a robust marker of NMDA function, mismatch negativity (MMN), in relation to changes in alcohol use patterns. Methods: Forty-six BD patients (aged 16-30) were recruited at baseline and 59% (n = 27) returned for follow-up 17.9 +/-7.3 months later. At both time-points a two-tone, passive, duration-deviant MMN paradigm was conducted and alcohol measures were collected. Pearson's correlations were performed between changes in MMN amplitudes and changes in alcohol use. Multiple regression was used to assess whether MMN amplitudes at baseline could predict alcohol use at follow-up. Results: Reduction in risky drinking patterns was associated with increased temporal MMN and decreased fronto-central MMN. Larger temporal MMN at baseline was a significant predictor of greater alcohol use at follow-up. Conclusions: Results suggest risky alcohol use in BD may further compound pre-existing NMDA receptor abnormalities and, importantly, reducing alcohol use early in stages of illness is associated with changes in MMN. This highlights the importance of monitoring alcohol use from first presentation. In addition, preliminary results present an exciting potential for utility of MMN as a neurobiological marker used to determine risk for alcohol misuse in BD. © 2015 The Author
Impaired causal awareness and associated cortical–basal ganglia structural changes in youth psychiatric disorders
No full textAbstractBackgroundCognitive impairments contribute significantly to disease burden in young individuals presenting with major psychiatric disorders. The capacity to encode the consequences of one's actions may be of particular importance for real-world functioning due to its fundamental role in goal-directed behavior.MethodsHere, we investigated a dimensional measure of causal awareness during a probabilistic learning task in 92 young individuals with an admixture of major mood and psychotic illnesses, at early and more established stages. Using automated gray matter segmentation of T1-weighted images, we estimated the volume and shapes of major subcortical structures and investigated their association with causal awareness.ResultsThe low causal awareness (LCA) group (n=35) reported increased social disability (p=.004) and reduced right pallidal size, specifically within the dorsolateral surfaces (p=.02), relative to the unimpaired high causal awareness (HCA) patients (n=57). In early-stage illness, LCA had a smaller right thalamus (p=.002) relative to HCA. Exploratory investigations suggested that in developed psychotic syndromes, causal awareness was correlated with left hippocampal size (p=.006) whereas, in more persistent affective disorders, causal awareness was correlated with left amygdala size (p=.013), specifically within the anterior aspect.DiscussionLow causal awareness occurs across diagnoses and stages of illness and is associated with poor functional outcomes. Our results suggest that there may be shared neural underpinnings of its dysfunction in the early course of mood and psychotic disorders, however in more established illness, there is greater neurobiological divergence in causal awareness correlates between diagnoses
Clinical and cognitive correlates of structural hippocampal change in "at-risk" older adults
No full textWith estimates of dementia expected to rise over the coming decades, there is interest in understanding the factors associated with promoting neuroprotection and limiting neurodegeneration. In this study, we examined the change in the volume of the hippocampus over a 2-month period in 34 older people "at risk" of cognitive decline (mean age = 66.8 years, 38% male). Factors that were examined included cognitive reserve, neuropsychological functioning, depression as well as a lifestyle (cognitive training) intervention. The results showed that over a 2-month period, increases in hippocampal size were associated with having higher premorbid intellect, greater occupational attainment, superior memory, and higher levels of functioning. Conversely, depression and disability were associated with decreases in hippocampal volume. Cognitive training was not associated with changes in hippocampal volume. These findings suggest that factors associated with cognitive reserve, cognition and depression may play an integral pathophysiological role in determining hippocampal volumes in "at-risk" older adults. © The Author(s) 2013
Mirroring cannot account for understanding action
No full textSusan Hurley's shared circuits model (SCM) rightly begins in action and progresses through a series of layers; but it fails to reach action understanding because it relies on mirroring as a driving force, draws on heavily criticized theories, and neglects the need for shared experience in our grasp of social understanding
